基于脑电通道动态选择方法的癫痫检测

Epilepsy detection based on the dynamic selection method of EEG channels

在癫痫检测任务中,脑电信号的通道选择直接影响检测性能。针对静态通道选择方法中脑电信号部分时段癫痫检测能力不足的问题,提出了动态通道选择方法。根据通道位置和脑电信号功率谱密度确定通道集合,选择通道集合中癫痫检测能力最强的一路通道作为特征提取通道,通过提高局部癫痫检测能力,进而提高整体检测能力。实验结果表明,提出的动态通道选择方法检测癫痫,取得了98.99%精确度、98.52%敏感度和99.52%特异度的较好性能。与多通道相比,检测性能相近,但特征提取通道最少,时间复杂度减少到O(1)。与单通道相比,精确度、敏感度和特异度性能指标提高4.93%以上。

In the task of epilepsy detection, the selection of EEG channel directly affects the detection performance. To solve the problem of weak detection ability in some periods of detection method using static channels, a dynamic channel selection method is proposed. The channel set is determined according to the channel position and power spectral density(PSD) of EEG. The channel with the strongest epileptic detection ability is selected as the feature extraction channel, which can enhance the overall detection ability by improving the local detection ability of epilepsy. Experimental results show that the dynamic channel selection method can detect epilepsy with 98.99% accuracy, 98.52% sensitivity and 99.52% specificity. Compared with multi-channel, the detection performance is similar. However, the feature extraction channel is the least, and the time complexity was reduced to O(1). Compared with single channel, the accuracy, sensitivity and specificity are improved more than 4.93%.